Summary
Summary {data-width=650}
Manhattan plot
manhattan_plot
QQ plot
qq_plot
AF plot
af_plot
P-Z plot
pz_plot
beta_std plot
beta_std_plot
Metadata
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}
LDSC
*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call:
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30640_raw/ukb-d-30640_raw.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30640_raw/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Mon Nov 25 14:59:25 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30640_raw/ukb-d-30640_raw.vcf.gz ...
Read summary statistics for 13585957 SNPs.
Dropped 12711 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1469 (0.0424)
Lambda GC: 1.3162
Mean Chi^2: 1.8975
Intercept: 1.0861 (0.0173)
Ratio: 0.096 (0.0192)
Analysis finished at Mon Nov 25 15:02:14 2019
Total time elapsed: 2.0m:49.06sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9521,
"inflation_factor": 1.2014,
"mean_EFFECT": 1.4852e-06,
"n": 342590,
"n_snps": 13585957,
"n_clumped_hits": 173,
"n_p_sig": 35034,
"n_mono": 0,
"n_ns": 1251778,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 569171,
"n_est": 343911.0675,
"ratio_se_n": 1.0019,
"mean_diff": 4.8226e-06,
"ratio_diff": 511.2522,
"sd_y_est1": 0.2347,
"sd_y_est2": 0.2351,
"r2_sum1": 0.0039,
"r2_sum2": 0.071,
"r2_sum3": 0.0707,
"r2_sum4": 0.0708,
"ldsc_nsnp_merge_refpanel_ld": 1283503,
"ldsc_nsnp_merge_regression_ld": 1283503,
"ldsc_observed_scale_h2_beta": 0.1469,
"ldsc_observed_scale_h2_se": 0.0424,
"ldsc_intercept_beta": 1.0861,
"ldsc_intercept_se": 0.0173,
"ldsc_lambda_gc": 1.3162,
"ldsc_mean_chisq": 1.8975,
"ldsc_ratio": 0.0959
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | TRUE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | TRUE |
| n_p_sig | TRUE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | FALSE |
| ldsc_intercept_beta | FALSE |
| n_clumped_hits | FALSE |
| r2_sum1 | FALSE |
| r2_sum2 | FALSE |
| r2_sum3 | FALSE |
| r2_sum4 | FALSE |
Definitions
General metrics
af_correlation: Correlation coefficient betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.n: Maximum value of reported sample size across all SNPs, \(n\).n_clumped_hits: Number of clumped hits.n_snps: Number of SNPsn_p_sig: Number of SNPs with pvalue below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations for<*>column.
se_n metrics
n_est: Estimated sample size value, \(\widehat{n}\).ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expectratio_se_nto be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.- \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
- \({z}_j = \frac{\beta_j}{{se}_j}\),
- and \(\beta_j\) is the reported effect size.
ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean ofdiffand the mean ofdiff2(expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.- \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
- \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.- \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
- \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
- and \({se}_j\) is the reported standard error.
sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.- \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
- \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).
LDSC metrics
Metrics from LD regression
ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.ldsc_observed_scale_h2_{beta,se}Coefficient value and SE for total observed scale h2.ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.ldsc_lambda_gc: Lambda GC statistics.ldsc_mean_chisq: Mean \(\chi^2\) statistics.ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).
Flags
When a metric needs attention, the flag should return TRUE.
af_correlation:abs(af_correlation)< 0.7.inflation_factor:inflation_factor> 1.2.n:n(max reported sample size) < 10000.is_snpid_non_unique: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_mean_chisq< 0.7.n_p_sig:n_p_sig> 1000.miss_<*>:n_miss_<*>/n_snps> 0.01.ldsc_ratio:ldsc_ratio> 0.5ldsc_intercept_beta:ldsc_intercept_beta> 1.5n_clumped_hits:n_clumped_hits> 1000r2_sum<*>:r2_sum<*>> 0.5
Plots
- Manhattan plot
- Red line: \(-log_{10}^{5 \times 10^{-8}}\)
- Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
- QQ plot
- AF plot
- P-Z plot
- beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)
Diagnostics
Details
Summary stats
| skim_type | skim_variable | n_missing | complete_rate | character.min | character.max | character.empty | character.n_unique | character.whitespace | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 0 | 1.0000000 | 3 | 94 | 0 | 13573910 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57082 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33337 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051233e+00 | 6.184960e+00 | 1.0000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.902570e+07 | 5.591520e+07 | 3.0200e+02 | 3.293104e+07 | 7.013916e+07 | 1.148602e+08 | 2.492309e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.500000e-06 | 3.470200e-03 | -1.5002e-01 | -9.859000e-04 | -1.300000e-06 | 9.884000e-04 | 8.050300e-02 | ▁▁▁▇▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.382100e-03 | 2.297800e-03 | 4.6620e-04 | 6.782000e-04 | 1.249800e-03 | 3.423300e-03 | 1.158300e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.691830e-01 | 2.984344e-01 | 0.0000e+00 | 2.036601e-01 | 4.597302e-01 | 7.279692e-01 | 1.000000e+00 | ▇▆▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.691825e-01 | 2.984347e-01 | 0.0000e+00 | 2.036545e-01 | 4.597290e-01 | 7.279725e-01 | 1.000000e+00 | ▇▆▆▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.908103e-01 | 2.544048e-01 | 1.0000e-03 | 7.431600e-03 | 6.004000e-02 | 2.953200e-01 | 9.989990e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 569171 | 0.9581059 | NA | NA | NA | NA | NA | 1.963399e-01 | 2.471029e-01 | 0.0000e+00 | 5.591000e-03 | 8.426520e-02 | 3.081070e-01 | 1.000000e+00 | ▇▂▁▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.425900e+05 | 0.000000e+00 | 3.4259e+05 | 3.425900e+05 | 3.425900e+05 | 3.425900e+05 | 3.425900e+05 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 692794 | rs530212009 | CA | C | -0.0010502 | 0.0009930 | 0.2902398 | 0.2902412 | 0.1105100 | 0.1894970 | 342590 |
| 1 | 693731 | rs12238997 | A | G | -0.0008560 | 0.0009379 | 0.3614099 | 0.3614077 | 0.1157900 | 0.1417730 | 342590 |
| 1 | 707522 | rs371890604 | G | C | -0.0012414 | 0.0010548 | 0.2392599 | 0.2392332 | 0.0972460 | 0.1293930 | 342590 |
| 1 | 717587 | rs144155419 | G | A | -0.0025836 | 0.0025190 | 0.3050598 | 0.3050589 | 0.0156520 | 0.0045926 | 342590 |
| 1 | 723329 | rs189787166 | A | T | 0.0025513 | 0.0074139 | 0.7307604 | 0.7307531 | 0.0017373 | 0.0003994 | 342590 |
| 1 | 730087 | rs148120343 | T | C | -0.0013208 | 0.0013070 | 0.3122497 | 0.3122278 | 0.0564170 | 0.0127796 | 342590 |
| 1 | 731718 | rs142557973 | T | C | -0.0010185 | 0.0008895 | 0.2522302 | 0.2522093 | 0.1216800 | 0.1543530 | 342590 |
| 1 | 732032 | rs61770163 | A | C | -0.0010348 | 0.0009492 | 0.2756398 | 0.2756283 | 0.1210900 | 0.1555510 | 342590 |
| 1 | 734349 | rs141242758 | T | C | -0.0009666 | 0.0008900 | 0.2774400 | 0.2774388 | 0.1209100 | 0.1525560 | 342590 |
| 1 | 740284 | rs61770167 | C | T | 0.0055796 | 0.0040825 | 0.1717200 | 0.1717157 | 0.0057552 | 0.0023962 | 342590 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154923311 | rs141127553 | C | T | -0.0007009 | 0.0010279 | 0.4953099 | 0.4953299 | 0.056212 | 0.0309934 | 342590 |
| 23 | 154923374 | rs111332691 | T | A | 0.0004043 | 0.0011284 | 0.7201401 | 0.7201292 | 0.044873 | 0.0116556 | 342590 |
| 23 | 154925045 | rs509981 | C | T | 0.0001697 | 0.0005436 | 0.7549705 | 0.7549655 | 0.245650 | 0.3634440 | 342590 |
| 23 | 154925895 | rs538470 | C | T | 0.0002377 | 0.0005561 | 0.6690507 | 0.6690450 | 0.241980 | 0.3634440 | 342590 |
| 23 | 154927581 | rs644138 | G | A | -0.0000526 | 0.0005112 | 0.9180301 | 0.9180293 | 0.302250 | 0.4635760 | 342590 |
| 23 | 154929412 | rs557132 | C | T | 0.0001561 | 0.0005438 | 0.7740197 | 0.7740166 | 0.245510 | 0.3568210 | 342590 |
| 23 | 154929637 | rs35185538 | CT | C | -0.0001491 | 0.0005676 | 0.7927806 | 0.7927755 | 0.229750 | 0.3011920 | 342590 |
| 23 | 154929952 | rs4012982 | CAA | C | 0.0002438 | 0.0005719 | 0.6698507 | 0.6698468 | 0.239490 | 0.3165560 | 342590 |
| 23 | 154930230 | rs781880 | A | G | 0.0001401 | 0.0005437 | 0.7966501 | 0.7966511 | 0.245910 | 0.3618540 | 342590 |
| 23 | 154930487 | rs781879 | T | A | 0.0000440 | 0.0018634 | 0.9811400 | 0.9811435 | 0.019562 | 0.1263580 | 342590 |
bcf preview
1 692794 rs530212009 CA C . PASS AF=0.11051 ES:SE:LP:AF:SS:ID -0.0010502:0.00099301:0.537243:0.11051:342590:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.11579 ES:SE:LP:AF:SS:ID -0.00085599:0.00093788:0.442:0.11579:342590:rs12238997
1 707522 rs371890604 G C . PASS AF=0.097246 ES:SE:LP:AF:SS:ID -0.0012414:0.0010548:0.62113:0.097246:342590:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015652 ES:SE:LP:AF:SS:ID -0.0025836:0.002519:0.515615:0.015652:342590:rs144155419
1 723329 rs189787166 A T . PASS AF=0.0017373 ES:SE:LP:AF:SS:ID 0.0025513:0.0074139:0.136225:0.0017373:342590:rs189787166
1 730087 rs148120343 T C . PASS AF=0.056417 ES:SE:LP:AF:SS:ID -0.0013208:0.001307:0.505498:0.056417:342590:rs148120343
1 731718 rs58276399 T C . PASS AF=0.12168 ES:SE:LP:AF:SS:ID -0.0010185:0.00088952:0.598203:0.12168:342590:rs58276399
1 732032 rs61770163 A C . PASS AF=0.12109 ES:SE:LP:AF:SS:ID -0.0010348:0.00094919:0.559658:0.12109:342590:rs61770163
1 734349 rs141242758 T C . PASS AF=0.12091 ES:SE:LP:AF:SS:ID -0.00096661:0.00088999:0.556831:0.12091:342590:rs141242758
1 740284 rs61770167 C T . PASS AF=0.0057552 ES:SE:LP:AF:SS:ID 0.0055796:0.0040825:0.765179:0.0057552:342590:rs61770167
1 742813 rs112573343 C T . PASS AF=0.0018623 ES:SE:LP:AF:SS:ID 0.014839:0.0077356:1.25899:0.0018623:342590:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.86981 ES:SE:LP:AF:SS:ID 0.00043576:0.00087745:0.207994:0.86981:342590:rs529266287
1 750230 rs190826124 G C . PASS AF=0.001514 ES:SE:LP:AF:SS:ID -0.0026527:0.0079926:0.130786:0.001514:342590:rs190826124
1 751343 rs28544273 T A . PASS AF=0.12287 ES:SE:LP:AF:SS:ID -0.00073596:0.00086892:0.401199:0.12287:342590:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.14269 ES:SE:LP:AF:SS:ID -0.00068143:0.00085881:0.369054:0.14269:342590:rs200141114
1 751756 rs28527770 T C . PASS AF=0.12298 ES:SE:LP:AF:SS:ID -0.00067992:0.0008677:0.363231:0.12298:342590:rs28527770
1 753405 rs3115860 C A . PASS AF=0.87097 ES:SE:LP:AF:SS:ID 0.00052202:0.00084566:0.269985:0.87097:342590:rs3115860
1 753425 rs3131970 T C . PASS AF=0.87553 ES:SE:LP:AF:SS:ID 0.00050323:0.00085959:0.253163:0.87553:342590:rs3131970
1 753541 rs2073813 G A . PASS AF=0.12856 ES:SE:LP:AF:SS:ID -0.00076771:0.00084774:0.437529:0.12856:342590:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0363 ES:SE:LP:AF:SS:ID -0.00049646:0.0015394:0.126633:0.0363:342590:rs12184325
1 754182 rs3131969 A G . PASS AF=0.87056 ES:SE:LP:AF:SS:ID 0.00060412:0.00084478:0.323736:0.87056:342590:rs3131969
1 754192 rs3131968 A G . PASS AF=0.87067 ES:SE:LP:AF:SS:ID 0.00061755:0.00084517:0.332566:0.87067:342590:rs3131968
1 754334 rs3131967 T C . PASS AF=0.87056 ES:SE:LP:AF:SS:ID 0.00061049:0.00084475:0.328022:0.87056:342590:rs3131967
1 754433 rs150578204 G A . PASS AF=0.0050485 ES:SE:LP:AF:SS:ID -0.0019496:0.0043332:0.185246:0.0050485:342590:rs150578204
1 754458 rs142682604 G T . PASS AF=0.0050155 ES:SE:LP:AF:SS:ID -0.0018612:0.0043447:0.174977:0.0050155:342590:rs142682604
1 755435 rs184270342 T G . PASS AF=0.0055515 ES:SE:LP:AF:SS:ID 0.0088839:0.0042134:1.45603:0.0055515:342590:rs184270342
1 755890 rs3115858 A T . PASS AF=0.87065 ES:SE:LP:AF:SS:ID 0.00054477:0.00084329:0.285436:0.87065:342590:rs3115858
1 756434 rs61768170 G C . PASS AF=0.12591 ES:SE:LP:AF:SS:ID -0.00070372:0.00086041:0.383609:0.12591:342590:rs61768170
1 756604 rs3131962 A G . PASS AF=0.87022 ES:SE:LP:AF:SS:ID 0.00055813:0.00084129:0.294941:0.87022:342590:rs3131962
1 757640 rs3115853 G A . PASS AF=0.8695 ES:SE:LP:AF:SS:ID 0.00067951:0.00084051:0.377962:0.8695:342590:rs3115853
1 757734 rs4951929 C T . PASS AF=0.87037 ES:SE:LP:AF:SS:ID 0.00057302:0.00084199:0.304387:0.87037:342590:rs4951929
1 757936 rs4951862 C A . PASS AF=0.87037 ES:SE:LP:AF:SS:ID 0.00057237:0.00084205:0.303923:0.87037:342590:rs4951862
1 758144 rs3131956 A G . PASS AF=0.87038 ES:SE:LP:AF:SS:ID 0.00057877:0.00084208:0.308132:0.87038:342590:rs3131956
1 758626 rs3131954 C T . PASS AF=0.87082 ES:SE:LP:AF:SS:ID 0.00057299:0.00084421:0.303373:0.87082:342590:rs3131954
1 759293 rs10157329 T A . PASS AF=0.098794 ES:SE:LP:AF:SS:ID -0.00077586:0.00098113:0.367472:0.098794:342590:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.0064352 ES:SE:LP:AF:SS:ID 0.0063563:0.0038081:1.02188:0.0064352:342590:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.87471 ES:SE:LP:AF:SS:ID 0.00058013:0.00085674:0.302492:0.87471:342590:rs3115851
1 761732 rs2286139 C T . PASS AF=0.86412 ES:SE:LP:AF:SS:ID 0.00066321:0.0008403:0.366562:0.86412:342590:rs2286139
1 761752 rs1057213 C T . PASS AF=0.8695 ES:SE:LP:AF:SS:ID 0.00069861:0.00084832:0.386994:0.8695:342590:rs1057213
1 762273 rs3115849 G A . PASS AF=0.86644 ES:SE:LP:AF:SS:ID 0.00057901:0.00084849:0.305404:0.86644:342590:rs3115849
1 762485 rs12095200 C A . PASS AF=0.098728 ES:SE:LP:AF:SS:ID -0.00067227:0.0010158:0.294068:0.098728:342590:rs12095200
1 762589 rs3115848 G C . PASS AF=0.87162 ES:SE:LP:AF:SS:ID 0.00063164:0.0008582:0.335621:0.87162:342590:rs3115848
1 762592 rs3131950 C G . PASS AF=0.87162 ES:SE:LP:AF:SS:ID 0.00063177:0.0008582:0.335697:0.87162:342590:rs3131950
1 762601 rs3131949 T C . PASS AF=0.87162 ES:SE:LP:AF:SS:ID 0.00063314:0.00085822:0.33661:0.87162:342590:rs3131949
1 762632 rs3131948 T A . PASS AF=0.87199 ES:SE:LP:AF:SS:ID 0.00064146:0.0008587:0.341941:0.87199:342590:rs3131948
1 764191 rs7515915 T G . PASS AF=0.1255 ES:SE:LP:AF:SS:ID -0.00079921:0.00085929:0.45305:0.1255:342590:rs7515915
1 766007 rs61768174 A C . PASS AF=0.1054 ES:SE:LP:AF:SS:ID -0.00083199:0.00093563:0.427268:0.1054:342590:rs61768174
1 766105 rs2519015 T A . PASS AF=0.85546 ES:SE:LP:AF:SS:ID 0.00067079:0.00083996:0.372102:0.85546:342590:rs2519015
1 767393 rs538667473 A C . PASS AF=0.0016562 ES:SE:LP:AF:SS:ID 0.0047082:0.0074326:0.278659:0.0016562:342590:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.83824 ES:SE:LP:AF:SS:ID -1.7472e-05:0.00082702:0.00738463:0.83824:342590:rs376645387